Progress on core outcomes sets for critical care research

Purpose of review: Appropriate selection and definition of outcome measures are essential for clinical trials to be maximally informative. Core outcome sets (an agreed, standardized collection of outcomes measured and reported in all trials for a specific clinical area) were developed due to established inconsistencies in trial outcome selection. This review discusses the rationale for, and methods of, core outcome set development, as well as current initiatives in critical care.

Recent findings: Recent systematic reviews of reported outcomes and measurement instruments relevant to the critically ill highlight inconsistencies in outcome selection, definition, and measurement, thus establishing the need for core outcome sets. Current critical care initiatives include development of core outcome sets for trials aimed at reducing mechanical ventilation duration; rehabilitation following critical illness; long-term outcomes in acute respiratory failure; and epidemic and pandemic studies of severe acute respiratory infection.

Summary: Development and utilization of core outcome sets for studies relevant to the critically ill is in its infancy compared to other specialties. Notwithstanding, core outcome set development frameworks and guidelines are available, several sets are in various stages of development, and there is strong support from international investigator-led collaborations including the International Forum for Acute Care Trialists.

Predictors of place of death for those in receipt of home-based palliative care services in Ontario, Canada

Many cancer patients die in institutional settings despite their preference to die at home. A longitudinal, prospective cohort study was conducted to comprehensively assess the determinants of home death for patients receiving home-based palliative care. Data collected from biweekly telephone interviews with caregivers (n=302) and program databases were entered into a multivariate logistic model. Patients with high nursing costs (odds ratio [OR]: 4.3; confidence interval [CI]: 1.8-10.2) and patients with high personal support worker costs (OR: 2.3; CI: 1.1-4.5) were more likely to die at home than those with low costs. Patients who lived alone were less likely to die at home than those who cohabitated (OR: 0.4; CI: 0.2-0.8), and those with a high propensity for a home-death preference were more likely to die at home than those with a low propensity (OR: 5.8; CI: 1.1-31.3). An understanding of the predictors of place of death may contribute to the development of effective interventions that support home death.

Implementation of Selective Packet Destruction on Wireless Open-Access Research Platform

Interesting wireless networking scenarios exist wherein network services must be guaranteed in a dynamic fashion for some priority users. For example, in disaster recovery, members need to be able to quickly block other users in order to gain sole use of the radio channel. As it is not always feasible to physically switch off other users, we propose a new approach, termed selective packet destruction (SPD) to ensure service for priority users. A testbed for SPD has been created, based on the Rice University Wireless open-Access Research Platform and been used to examine the feasibility of our approach. Results from the testbed are presented to demonstrate the feasibility of SPD and show how a balance between performance and acknowledgement destruction rate can be achieved. A 90% reduction in TCP & UDP traffic is achieved for a 75% MAC ACK destruction rate.

The effect of probe interval estimation on attack detection performance of a WLAN independent intrusion detection system

A new niche of densely populated, unprotected networks is becoming more prevalent in public areas such as Shopping Malls, defined here as independent open-access networks, which have attributes that make attack detection more challenging than in typical enterprise networks. To address these challenges, new detection systems which do not rely on knowledge of internal device state are investigated here. This paper shows that this lack of state information requires an additional metric (The exchange timeout window) for detection of WLAN Denial of Service Probe Flood attacks. Variability in this metric has a significant influence on the ability of a detection system to reliably detect the presence of attacks. A parameter selection method is proposed which is shown to provide reliability and repeatability in attack detection in WLANs. Results obtained from ongoing live trials are presented that demonstrate the importance of accurately estimating probe request and probe response timeouts in future Independent Intrusion Detection Systems.

The Coxian phase-type distribution as a contribution to the multilevel model of in-hospital mortality

This paper presents multilevel models that utilize the Coxian phase-type distribution in order to be able to include a survival component in the model. The approach is demonstrated by modeling patient length of stay and in-hospital mortality in geriatric wards in Italy. The multilevel model is used to provide a means of controlling for the existence of possible intra-ward correlations, which may make patients within a hospital more alike in terms of experienced outcome than patients coming from different hospitals, everything else being equal. Within this multilevel model we introduce the use of the Coxian phase-type distribution to create a covariate that represents patient length of stay or stage (of hospital care). Results demonstrate that the use of the multilevel model for representing the in-patient mortality is successful and further enhanced by the inclusion of the Coxian phase-type distribution variable (stage covariate).

Using the hidden Markov model to capture quality of care in Lombardy geriatric wards

Quality of care is an important aspect of healthcare monitoring, which is used to ensure that the healthcare system is delivering care of the highest standard. With populations growing older there is an increased urgency in making sure that the healthcare delivered is of the highest standard. Healthcare providers are under increased pressure to ensure that this is the case with public and government demand expecting a healthcare system of the highest quality. Modelling quality of care is difficult to measure due to the many ways of defining it. This paper introduces a potential model which could be used to take quality of care into account when modelling length of stay. The Coxian phase-type distribution is used to model length of stay and the associated quality of care incorporated into the Coxian using a Hidden Markov model. Covariates are also introduced to determine their impact on the hidden level to find out what potentially can affect quality of care. This model is applied to geriatic patient data from the Lombardy region of Italy. The results obtained highlighted that bed numbers and the type of hospital (public or private) can have an effect on the quality of care delivered.

A Conditional Approach for Modelling Patient Re-admissions in Hospital using a mixture of Coxian phase-type distributions incorporating Bayes Theorem

The number of elderly patients requiring hospitalisation in Europe is rising. With a greater proportion of elderly people in the population comes a greater demand for health services and, in particular, hospital care. Thus, with a growing number of elderly patients requiring hospitalisation competing with non-elderly patients for a fixed (and in some cases, decreasing) number of hospital beds, this results in much longer waiting times for patients, often with a less satisfactory hospital experience. However, if a better understanding of the recurring nature of elderly patient movements between the community and hospital can be developed, then it may be possible for alternative provisions of care in the community to be put in place and thus prevent readmission to hospital. The research in this paper aims to model the multiple patient transitions between hospital and community by utilising a mixture of conditional Coxian phase-type distributions that incorporates Bayes' theorem. For the purpose of demonstration, the results of a simulation study are presented and the model is applied to hospital readmission data from the Lombardy region of Italy.

Discrete Conditional Phase-type Model Utilising a Multiclass Support Vector Machine for the Prediction of Retinopathy of Prematurity

Retinopathy of prematurity (ROP) is a rare disease in which retinal blood vessels of premature infants fail to develop normally, and is one of the major causes of childhood blindness throughout the world. The Discrete Conditional Phase-type (DC-Ph) model consists of two components, the conditional component measuring the inter-relationships between covariates and the survival component which models the survival distribution using a Coxian phase-type distribution. This paper expands the DC-Ph models by introducing a support vector machine (SVM), in the role of the conditional component. The SVM is capable of classifying multiple outcomes and is used to identify the infant's risk of developing ROP. Class imbalance makes predicting rare events difficult. A new class decomposition technique, which deals with the problem of multiclass imbalance, is introduced. Based on the SVM classification, the length of stay in the neonatal ward is modelled using a 5, 8 or 9 phase Coxian distribution.

Treatment of retinopathy of prematurity in Northern Ireland, 2000-2011: a population-based study

Purpose To evaluate the incidence of treatment-requiring retinopathy of prematurity (ROP) over a 12-year-period in Northern Ireland. Methods The medical records of all infants treated for ROP from January 2000 to December 2011were retrospectively reviewed and cross-referenced with the Neonatal Intensive Care Outcomes Research and Evaluation (NICORE) database. Results The Northern Ireland population data showed an increase in the number of live births from 2000 to 2011. The proportion of babies born with a birth weight <1501 g and/or <32 weeks’ gestational age remained constant (χ2 trend = 3.220, P = 0.0727), although the proportion of these babies who died prior to 42 weeks’ gestation decreased from 2000 to 2011 (P = 0.0196 using χ2 for trend = 5.445; P = 0.0354 using χ2 = 20.809). The prevalence of treatment-requiring ROP in these infants increased from 1.05% in 2000 to 5.78% in 2011 (P < 0.001 using χ2 trend = 16.309; P < 0.001 using χ2 = 31.378). Conclusions The present population-based study highlights that the incidence of treatment- requiring ROP is increasing in Northern Ireland. The increasing number of infants requiring treatment will need to be taken into consideration in the commissioning process for ROP services in Northern Ireland.

Hospitalization in Geriatric Wards: Considerations on the Evaluation of the Outcome

Within a defined law framework, the Italian central health system dictates the standards for hospitalization to local care units, which are in turn allowed to establish their own effectiveness criteria. The appropriateness of the hospitalization decision is therefore predetermined at patients admission, whereas its effectiveness relies on the ex post patient well-being as a result of the complex system of reciprocal relations between patients and healthcare agents at the ward level. We consider the outcomes in geriatric wards referring to the national health system, with respect both to patients traits at the individual level and wards/hospital settings. The risk that models the healthcare outcome is accordingly adjusted for covariates at the different levels of analysis (Goldstein & Spiegelhalter, 1996), thus allowing to differentiate among outcomes in terms of the hospitalization structure and, when appropriate, of territorial aggregation.

Environmental and social supply chain management sustainability practices: construct development and measurement

The purpose of this paper is to conceptualise and operationalise the concept of supply chain management sustainability practices. Based on a multi-stage procedure involving a literature review, expert Q-sort and pre-test process, pilot test and survey of 156 supply chain directors and managers in Ireland, we develop a multidimensional conceptualisation and measure of social and environmental supply chain management sustainability practices. The research findings show theoretically sound constructs based on four underlying sustainable supply chain management practices: monitoring, implementing systems, new product and process development and strategy redefinition. A two-factor model is then identified as the most reliable: comprising process-based and market-based practices.